If you are new to MNE, consider first reading the Cookbook, as it
gives some simple steps for starting with analysis. The other sections provide
more in-depth information about how to use the software.
You can also jump to the Python API Reference for specific Python function
and class usage information.
A quick run-through of the basic steps involved in M/EEG source analysis.
Reading your data
How to get your raw data loaded in MNE.
Dealing with artifacts and noise sources in data.
Projecting raw data into source (brain) space.
Decomposing time-domain signals into time-frequency representations.
Using parametric and non-parametric tests with M/EEG data.
How to use dataset fetchers for public data
Additional information about various MNE-C tools.
Information about the MATLAB toolbox.
More details about our implementations and software.